Reputation: 5591
When I run the line below, the NaN number in the dataframe does not get modified. Utilizing the exact same argument with .to_csv()
, I get the expected result. Does .to_html
require something different?
df.to_html('file.html', float_format='{0:.2f}'.format, na_rep="NA_REP")
Upvotes: 5
Views: 2702
Reputation: 13757
It looks like the float_format
doesn't play nice with na_rep
. However, you can work around it if you pass a function to float_format
that conditionally handles your NaNs along with the float formatting you want:
>>> df
Group Data
0 A 1.2225
1 A NaN
Reproducing your problem:
>>> out = StringIO()
>>> df.to_html(out,na_rep="Ted",float_format='{0:.2f}'.format)
>>> out.getvalue()
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>Group</th>
<th>Data</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td> A</td>
<td>1.22</td>
</tr>
<tr>
<th>1</th>
<td> A</td>
<td> nan</td>
</tr>
</tbody>
So you get the proper float precision but not the correct na_rep
. But the following seems to work:
>>> out = StringIO()
>>> fmt = lambda x: '{0:.2f}'.format(x) if pd.notnull(x) else 'Ted'
>>> df.to_html(out,float_format=fmt)
>>> out.getvalue()
<table border="1" class="dataframe">
<thead>
<tr style="text-align: right;">
<th></th>
<th>Group</th>
<th>Data</th>
</tr>
</thead>
<tbody>
<tr>
<th>0</th>
<td> A</td>
<td>1.22</td>
</tr>
<tr>
<th>1</th>
<td> A</td>
<td> Ted</td>
</tr>
</tbody>
</table>
Upvotes: 5